Abstract: Yogyakarta, as the capital city of Yogyakarta Province, has important roles in various sectors that require good provision of public transportation system. Ideally, a good transportation system should be able to accommodate the amount of travel demand. This research attempts to develop a trip generation model to predict the number of public transport passenger in Yogyakarta city. The model is built by using multiple linear regression analysis, which establishes relationship between trip number and socioeconomic attributes. The data consist of primary and secondary data. Primary data was collected by conducting household surveys which randomly selected. The resulted model is further applied to evaluate the existing TransJogja, a new Bus Rapid Transit system serves Yogyakarta and surrounding cities, shelters.
Abstract: This study aims to assess the potential of solar energy technology for improving access to water and hence the livelihood strategies of rural communities in Baja California Sur, Mexico. It focuses on livestock ranches and photovoltaic water-pumptechnology as well as other water extraction methods. The methodology used are the Sustainable Livelihoods and the Appropriate Technology approaches. A household survey was applied in June of 2006 to 32 ranches in the municipality, of which 22 used PV pumps; and semi-structured interviews were conducted. Findings indicate that solar pumps have in fact helped people improve their quality of life by allowing them to pursue a different livelihood strategy and that improved access to water -not necessarily as more water but as less effort to extract and collect it- does not automatically imply overexploitation of the resource; consumption is based on basic needs as well as on storage and pumping capacity. Justification for such systems lies in the avoidance of logistical problems associated to fossil fuels, PV pumps proved to be the most beneficial when substituting gasoline or diesel equipment but of dubious advantage if intended to replace wind or gravity systems. Solar water pumping technology-s main obstacle to dissemination are high investment and repairs costs and it is therefore not suitable for all cases even when insolation rates and water availability are adequate. In cases where affordability is not an obstacle it has become an important asset that contributes –by means of reduced expenses, less effort and saved time- to the improvement of livestock, the main livelihood provider for these ranches.
Abstract: Optimization of a microwave-assisted extraction of cherry laurel (Prunus laurocerasus) fruit using methanol was studied. The influence of process parameters (microwave power, plant material-to-solvent ratio and the extraction time) on the extraction efficiency were optimized by using response surface methodology. The predicted maximum yield of extractive substances (41.85 g/100 g fresh plant material) was obtained at microwave power of 600 W and plant material to solvent ratio of 0.2 g/cm3 after 26 minutes of extraction, while a mean value of 40.80±0.41 g/100 g fresh plant material was obtained from laboratory experiments. This proves applicability of the model in predicting optimal extraction conditions with minimal laborious and time consuming. The results indicated that all process parameters were effective on the extraction efficiency, while the most important factor was extraction time. In order to rationalize production the optimal economical condition which gave a large total extract yield with minimal energy and solvent consumption was found.
Abstract: Identification of cancer genes that might anticipate
the clinical behaviors from different types of cancer disease is
challenging due to the huge number of genes and small number of
patients samples. The new method is being proposed based on
supervised learning of classification like support vector machines
(SVMs).A new solution is described by the introduction of the
Maximized Margin (MM) in the subset criterion, which permits to
get near the least generalization error rate. In class prediction
problem, gene selection is essential to improve the accuracy and to
identify genes for cancer disease. The performance of the new
method was evaluated with real-world data experiment. It can give
the better accuracy for classification.
Abstract: This paper examines the available experiment data for a copper bromide vapor laser (CuBr laser), emitting at two wavelengths - 510.6 and 578.2nm. Laser output power is estimated based on 10 independent input physical parameters. A classification and regression tree (CART) model is obtained which describes 97% of data. The resulting binary CART tree specifies which input parameters influence considerably each of the classification groups. This allows for a technical assessment that indicates which of these are the most significant for the manufacture and operation of the type of laser under consideration. The predicted values of the laser output power are also obtained depending on classification. This aids the design and development processes considerably.
Abstract: The paper presents an on-line recognition machine
(RM) for continuous/isolated, dynamic and static gestures that arise
in Flight Deck Officer (FDO) training. RM is based on generic pattern
recognition framework. Gestures are represented as templates using
summary statistics. The proposed recognition algorithm exploits temporal
and spatial characteristics of gestures via dynamic programming
and Markovian process. The algorithm predicts corresponding index
of incremental input data in the templates in an on-line mode.
Accumulated consistency in the sequence of prediction provides a
similarity measurement (Score) between input data and the templates.
The algorithm provides an intuitive mechanism for automatic detection
of start/end frames of continuous gestures. In the present paper,
we consider isolated gestures. The performance of RM is evaluated
using four datasets - artificial (W TTest), hand motion (Yang) and
FDO (tracker, vision-based ). RM achieves comparable results which
are in agreement with other on-line and off-line algorithms such as
hidden Markov model (HMM) and dynamic time warping (DTW).
The proposed algorithm has the additional advantage of providing
timely feedback for training purposes.
Abstract: Prediction of sinusoidal signals with time-varying
frequencies has been an important research topic in power electronics
systems. To solve this problem, we propose a new fuzzy
predictive filtering scheme, which is based on a Finite Impulse
Response (FIR) filter bank. Fuzzy logic is introduced here to provide
appropriate interpolation of individual filter outputs. Therefore,
instead of regular 'hard' switching, our method has the advantageous
'soft' switching among different filters. Simulation
comparisons between the fuzzy predictive filtering and conventional
filter bank-based approach are made to demonstrate that the
new scheme can achieve an enhanced prediction performance for
slowly changing sinusoidal input signals.
Abstract: Studies in economics domain tried to reveal the correlation between stock markets. Since the globalization era, interdependence between stock markets becomes more obvious. The Dynamic Interaction Network (DIN) algorithm, which was inspired by a Gene Regulatory Network (GRN) extraction method in the bioinformatics field, is applied to reveal important and complex dynamic relationship between stock markets. We use the data of the stock market indices from eight countries around the world in this study. Our results conclude that DIN is able to reveal and model patterns of dynamic interaction from the observed variables (i.e. stock market indices). Furthermore, it is also found that the extracted network models can be utilized to predict movement of the stock market indices with a considerably good accuracy.
Abstract: In the present study, computational fluid dynamics
(CFD) simulation has been executed to investigate the transition
boundaries of different flow patterns for moderately viscous oil-water
(viscosity ratio 107, density ratio 0.89 and interfacial tension of 0.032
N/m.) two-phase flow through a horizontal pipeline with internal
diameter and length of 0.025 m and 7.16 m respectively. Volume of
Fluid (VOF) approach including effect of surface tension has been
employed to predict the flow pattern. Geometry and meshing of the
present problem has been drawn using GAMBIT and ANSYS
FLUENT has been used for simulation. A total of 47037 quadrilateral
elements are chosen for the geometry of horizontal pipeline. The
computation has been performed by assuming unsteady flow,
immiscible liquid pair, constant liquid properties, co-axial flow and a
T-junction as entry section. The simulation correctly predicts the
transition boundaries of wavy stratified to stratified mixed flow.
Other transition boundaries are yet to be simulated. Simulated data
has been validated with our own experimental results.
Abstract: In this paper, we have presented a new multivariate fuzzy time series forecasting method. This method assumes mfactors with one main factor of interest. History of past three years is used for making new forecasts. This new method is applied in forecasting total number of car accidents in Belgium using four secondary factors. We also make comparison of our proposed method with existing methods of fuzzy time series forecasting. Experimentally, it is shown that our proposed method perform better than existing fuzzy time series forecasting methods. Practically, actuaries are interested in analysis of the patterns of causalities in road accidents. Thus using fuzzy time series, actuaries can define fuzzy premium and fuzzy underwriting of car insurance and life insurance for car insurance. National Institute of Statistics, Belgium provides region of risk classification for each road. Thus using this risk classification, we can predict premium rate and underwriting of insurance policy holders.
Abstract: Schools today face ever-increasing demands in their attempts to ensure that students are well equipped to enter the workforce and navigate a complex world. Research indicates that computer technology can help support learning, implementation of various experiments or learning games, and that it is especially useful in developing the higher-order skills of critical thinking, observation, comprehension, implementation, comparison, analysis and active attention to activities such as research, field work, simulations and scientific inquiry. The ICT in education supports the learning procedure by enabling it to be more flexible and effective, create a rich and attractive training environment and equip the students with knowledge and potential useful for the competitive social environment in which they live. This paper presents the design, the development, and the results of the evaluation analysis of an interactive educational game which using real electric vehicles - toys (material) on a toy race track. When the game starts each student selects a specific vehicle toy. Then students are answering questionnaires in the computer. The vehicles' speed is related to the percentage of right answers in a multiple choice questionnaire (software). Every question has its own significant value depending of the different level of questionnaire. Via the developed software, each right or wrong answers in questionnaire increase or decrease the real time speed of their vehicle toys. Moreover the rate of vehicle's speed increase or decrease depends on the difficulty level of each question. The aim of the work is to attract the student’s interest in a learning process and also to improve their scores. The developed real time game was tested using independent populations of students of age groups: 8-10, 11-14, 15-18 years. Standard educational and statistical analysis tools were used for the evaluation analysis of the game. Results reveal that students using the developed real time control game scored much higher (60%) than students using a traditional simulation game on the same questionnaire. Results further indicate that student's interest in repeating the developed real time control gaming was far higher (70%) than the interest of students using a traditional simulation game.
Abstract: In order to better understand the performance of
screen channel liquid acquisition devices (LADs) in liquid oxygen (LOX), a computational fluid dynamics (CFD) simulation of LOX passing through a LAD screen channel was conducted. In the
simulation, the screen is taken as a 'porous jump' where the pressure
drop across the screen depends on the incoming velocity and is formulated by Δp = Av + Bv2
. The CFD simulation reveals the importance of the pressure losses due to the flow entering from
across the screen and impacting and merging with the channel flow
and the vortices in the channel to the cumulative flow resistance. In fact, both the flow resistance of flows impact and mergence and the
resistance created by vortices are much larger than the friction and dynamic pressure losses in the channel and are comparable to the
flow resistance across the screen. Therefore, these resistances in the
channel must be considered as part of the evaluation for the LAD
channel performance. For proper operation of a LAD in LOX these resistances must be less than the bubble point pressure for the screen
channel in LOX. The simulation also presents the pressure and velocity distributions within the LAD screen channel, expanding the understanding of the fluid flow characteristics within the channel.
Abstract: Strict stability can present the rate of decay of the
solution, so more and more investigators are beginning to study the
topic and some results have been obtained. However, there are few
results about strict stability of stochastic differential equations. In
this paper, using Lyapunov functions and Razumikhin technique, we
have gotten some criteria for the strict stability of impulsive stochastic
functional differential equations with markovian switching.
Abstract: The migration of a deformable drop in simple shear
flow at finite Reynolds numbers is investigated numerically by
solving the full Navier-Stokes equations using a finite
difference/front tracking method. The objectives of this study are to
examine the effectiveness of the present approach to predict the
migration of a drop in a shear flow and to investigate the behavior of
the drop migration with different drop sizes and non-unity viscosity
ratios. It is shown that the drop deformation depends strongly on the
capillary number, so that; the proper non-dimensional number for the
interfacial tension is the capillary number. The rate of migration
increased with increasing the drop radius. In other words, the
required time for drop migration to the centreline decreases. As the
viscosity ratio increases, the drop rotates more slowly and the
lubrication force becomes stronger. The increased lubrication force
makes it easier for the drop to migrate to the centre of the channel.
The migration velocity of the drop vanishes as the drop reaches the
centreline under viscosity ratio of one and non-unity viscosity ratios.
To validate the present calculations, some typical results are
compared with available experimental and theoretical data.
Abstract: In this chapter, we have studied Variation of velocity in incompressible fluid over a moving surface. The boundary layer equations are on a fixed or continuously moving flat plate in the same or opposite direction to the free stream with suction and injection. The boundary layer equations are transferred from partial differential equations to ordinary differential equations. Numerical solutions are obtained by using Runge-Kutta and Shooting methods. We have found numerical solution to velocity and skin friction coefficient.
Abstract: Job stress is one of the most important concepts for
the today-s corporate as well as institutional world. The current study
is conducted to identify the causes of faculty stress at Higher
Education in Pakistan. For the purpose, Public & Private Business
Schools of Punjab is selected as representative of Pakistan. A sample
of 300 faculty members (214 males, 86 females) responded to the
survey. Regression analysis shows that the Workload, Student
Related issues and Role Conflicts are the major sources contributing
significantly towards producing stress. The study also revealed that
Private sector faculty members experienced more stress as compared
to faculty in Public sector Business Schools. Moreover, females,
younger ages, lower designation & low qualification faculty
members experience more stress as compared to males, older ages,
higher designation and high qualification. The study yield many
significant results for the policy makers of Business Institutions.
Abstract: OLAP uses multidimensional structures, to provide
access to data for analysis. Traditionally, OLAP operations are more
focused on retrieving data from a single data mart. An exception is
the drill across operator. This, however, is restricted to retrieving
facts on common dimensions of the multiple data marts. Our concern
is to define further operations while retrieving data from multiple
data marts. Towards this, we have defined six operations which
coalesce data marts. While doing so we consider the common as well
as the non-common dimensions of the data marts.
Abstract: The main purpose of this study is to analyze climbers
involved in motivation and risk perception and analysis of the
predictive ability of the risk perception "mountaineering" involved in
motivation. This study used questionnaires, to have to climb the
3000m high mountain in Taiwan climbers object to carry out an
investigation in order to non-random sampling, a total of 231 valid
questionnaires were. After statistical analysis, the study found that: 1.
Climbers the highest climbers involved in motivation "to enjoy the
natural beauty of the fun. 2 climbers for climbers "risk perception" the
highest: the natural environment of risk. 3. Climbers “seeking
adventure stimulate", “competence achievement" motivation highly
predictive of risk perception. Based on these findings, this study not
only practices the recommendations of the outdoor leisure industry,
and also related research proposals for future researchers.
Abstract: The African Great Lakes Region refers to the zone
around lakes Victoria, Tanganyika, Albert, Edward, Kivu, and
Malawi. The main source of electricity in this region is hydropower
whose systems are generally characterized by relatively weak,
isolated power schemes, poor maintenance and technical deficiencies
with limited electricity infrastructures. Most of the hydro sources are
rain fed, and as such there is normally a deficiency of water during
the dry seasons and extended droughts. In such calamities fossil fuels
sources, in particular petroleum products and natural gas, are
normally used to rescue the situation but apart from them being nonrenewable,
they also release huge amount of green house gases to our
environment which in turn accelerates the global warming that has at
present reached an amazing stage. Wind power is ample, renewable,
widely distributed, clean, and free energy source that does not
consume or pollute water. Wind generated electricity is one of the
most practical and commercially viable option for grid quality and
utility scale electricity production. However, the main shortcoming
associated with electric wind power generation is fluctuation in its
output both in space and time. Before making a decision to establish
a wind park at a site, the wind speed features there should therefore
be known thoroughly as well as local demand or transmission
capacity. The main objective of this paper is to utilise monthly
average wind speed data collected from one prospective site within
the African Great Lakes Region to demonstrate that the available
wind power there is high enough to generate electricity. The mean
monthly values were calculated from records gathered on hourly
basis for a period of 5 years (2001 to 2005) from a site in Tanzania.
The documentations that were collected at a height of 2 m were
projected to a height of 50 m which is the standard hub height of
wind turbines. The overall monthly average wind speed was found to
be 12.11 m/s whereas June to November was established to be the
windy season as the wind speed during the session is above the
overall monthly wind speed. The available wind power density
corresponding to the overall mean monthly wind speed was evaluated
to be 1072 W/m2, a potential that is worthwhile harvesting for the
purpose of electric generation.
Abstract: A new approach to predict the 3D structures of proteins by combining the knowledge-based method and Molecular Dynamics Simulation is presented on the chicken villin headpiece subdomain (HP-36). Comparative modeling is employed as the knowledge-based method to predict the core region (Ala9-Asn28) of the protein while the remaining residues are built as extended regions (Met1-Lys8; Leu29-Phe36) which then further refined using Molecular Dynamics Simulation for 120 ns. Since the core region is built based on a high sequence identity to the template (65%) resulting in RMSD of 1.39 Å from the native, it is believed that this well-developed core region can act as a 'nucleation center' for subsequent rapid downhill folding. Results also demonstrate that the formation of the non-native contact which tends to hamper folding rate can be avoided. The best 3D model that exhibits most of the native characteristics is identified using clustering method which then further ranked based on the conformational free energies. It is found that the backbone RMSD of the best model compared to the NMR-MDavg is 1.01 Å and 3.53 Å, for the core region and the complete protein, respectively. In addition to this, the conformational free energy of the best model is lower by 5.85 kcal/mol as compared to the NMR-MDavg. This structure prediction protocol is shown to be effective in predicting the 3D structure of small globular protein with a considerable accuracy in much shorter time compared to the conventional Molecular Dynamics simulation alone.